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  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "# Learn OpenAI Whisper - Chapter 3\n",
        "\n",
        "## Complementary introduction to audio data processing with Hugging Face and Whisper\n",
        "\n",
        "\n",
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/1bIiGyv_YiTdq97a7KrowCceOrZlG2hXL)\n",
        "\n",
        "In this notebook, we'll explore the essentials of working with audio data in Python, leveraging the power of Hugging Face's `datasets` library and OpenAI's Whisper model. Our journey will take us through setting up a Hugging Face account, loading and exploring an audio dataset, preprocessing that dataset to meet the requirements of machine learning models, and finally, transcribing audio to text using the state-of-the-art Whisper model.\n",
        "\n",
        "Audio data processing is a pivotal step in numerous machine learning applications, from developing voice-activated assistants to creating systems capable of understanding and transcribing spoken language in real-time. By the end of this notebook, you'll have a solid foundation in handling audio data, which you can apply to a wide range of natural language processing tasks.\n"
      ],
      "metadata": {
        "id": "fFBjlhsX3lqU"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Setting up a Hugging Face account\n",
        "\n",
        "To access and utilize the vast array of datasets and machine learning models available on Hugging Face, an account is required. A Hugging Face account offers not just access to datasets like \"PolyAI/minds14\" but also allows for collaboration on projects, contribution to the community through dataset/model sharing, and even tracking progress on various machine learning tasks. Follow the steps outlined above to create your account and get started with Hugging Face.\n",
        "\n",
        "## To create a Hugging Face account, you can follow these simple steps:\n",
        "<img src=\"https://github.com/PacktPublishing/Learn-OpenAI-Whisper/raw/main/Chapter03/hugging_face_join.png\" width=250>\n",
        "\n",
        "1. Go to the Hugging Face website.\n",
        "2. Click on “Sign Up” or go to https://huggingface.co/join\n",
        "3. Enter your email address and password (you can skip the prompt to \"Join organization\").\n",
        "4. If you already have an account, click on “Log in”.\n",
        "5. To interact with the Hub, you need to be logged in with a Hugging Face account.\n",
        "\n",
        "## To create a Hugging Face Access Token\n",
        "<img src=\"https://github.com/PacktPublishing/Learn-OpenAI-Whisper/raw/main/Chapter03/hugging_face_settings_menu_option.png\" width=650>\n",
        "<img src=\"https://github.com/PacktPublishing/Learn-OpenAI-Whisper/raw/main/Chapter03/hugging_face_create_token.png\" width=250>\n",
        "\n",
        "1. Go to the Access Tokens tab in your Hugging Face settings.\n",
        "2. Click on the New token button to create a new User Access Token.\n",
        "3. Select the `write` role and a name for your token. This notebook only needs a `read` role; however, we will be writing to Hugging Face in [Chapter 4](https://colab.research.google.com/drive/1LADNomT0JUBCsopU6r_NsZfOaNiz2N3h).\n",
        "\n",
        "## OPTIONAL: To authenticate your identity using your \"Secrets\" in Colab\n",
        "<img src=\"https://github.com/PacktPublishing/Learn-OpenAI-Whisper/raw/main/Chapter03/hugging_face_token_notebook_access.png\" width=450>\n",
        "\n",
        "1. In your Colab notebook, click on the key icon on the left to add a new secret.\n",
        "2. Set the name of the secret to HF_TOKEN.\n",
        "3. Paste your Hugging Face token value in the Value field.\n",
        "4. Click Add to save the secret.\n",
        "5. Turn ON \"Notebook access\".\n",
        "\n",
        "You can now use the secret token in your Colab notebook to authenticate. Make sure to keep your token private and not share it with anyone else. Happy coding! 😊"
      ],
      "metadata": {
        "id": "VCEKs-Y4wAYQ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Load and explore an audio dataset\n",
        "In this section, we dive into loading and exploring an audio dataset using the `datasets` library. Specifically, we're working with the \"PolyAI/minds14\" dataset, a rich collection of audio recordings intended for intent classification tasks—crucial for building voice-operated interfaces and understanding natural language commands. Through the code snippets below, we inspect the dataset's structure, listen to audio samples directly within the notebook, and employ visualization techniques to analyze the audio signals. This hands-on exploration is foundational for grasping the nuances of audio data in machine learning applications.\n"
      ],
      "metadata": {
        "id": "RE6ewF9z4r2l"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Install datasets library with audio support\n",
        "To begin working with audio datasets, we first need to install the `datasets` library, ensuring we include support for audio data.\n",
        "This is done by specifying `[audio]` after the library name, which installs additional dependencies necessary for audio processing."
      ],
      "metadata": {
        "id": "j4VqBDxt6vEg"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "1B8bm_3ouldO"
      },
      "outputs": [],
      "source": [
        "%%capture\n",
        "!pip install pyarrow==14.0.2\n",
        "!pip install datasets[audio]"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Setting environment variables for Hugging Face authentication\n",
        "Next, we set up our environment to authenticate with Hugging Face. This involves storing our Hugging Face API token as an environment variable. This token allows us to access Hugging Face's datasets and models securely.\n",
        "\n",
        "#### Option 1: Authenticate via Huggig Face's notebook_login class by copying the token from the Hugging Face website and pasting it at the prompt:\n",
        "\n",
        "```\n",
        "from huggingface_hub import notebook_login\n",
        "notebook_login()\n",
        "```\n",
        "#### Option 2: You can also authenticate using the Hugging Face's CLI command\n",
        "```\n",
        "!huggingface-cli login\n",
        "```\n",
        "<img src=\"https://github.com/PacktPublishing/Learn-OpenAI-Whisper/raw/main/Chapter03/hugging_face_cli_authenticate.png\" width=850>\n",
        "\n",
        "Run either option 1, or 2, then verify using:\n",
        "```\n",
        "from huggingface_hub import whoami\n",
        "whoami()\n",
        "```\n"
      ],
      "metadata": {
        "id": "hSY7Cv2A61tN"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Option 1 - Enter your token in the output prompt below and hit enter on Windows or return on Mac\n",
        "from huggingface_hub import notebook_login\n",
        "notebook_login()"
      ],
      "metadata": {
        "id": "bumGSQCMDizB"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Option 2 - Enter your token in the output prompt below and hit enter on Windows or return on Mac\n",
        "!huggingface-cli login"
      ],
      "metadata": {
        "id": "OHNuVY_RTujq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "eaa29b51-19e5-4cb0-afbd-d4210dc925a0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "    _|    _|  _|    _|    _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|_|_|_|    _|_|      _|_|_|  _|_|_|_|\n",
            "    _|    _|  _|    _|  _|        _|          _|    _|_|    _|  _|            _|        _|    _|  _|        _|\n",
            "    _|_|_|_|  _|    _|  _|  _|_|  _|  _|_|    _|    _|  _|  _|  _|  _|_|      _|_|_|    _|_|_|_|  _|        _|_|_|\n",
            "    _|    _|  _|    _|  _|    _|  _|    _|    _|    _|    _|_|  _|    _|      _|        _|    _|  _|        _|\n",
            "    _|    _|    _|_|      _|_|_|    _|_|_|  _|_|_|  _|      _|    _|_|_|      _|        _|    _|    _|_|_|  _|_|_|_|\n",
            "\n",
            "    To login, `huggingface_hub` requires a token generated from https://huggingface.co/settings/tokens .\n",
            "Token: \n",
            "Add token as git credential? (Y/n) n\n",
            "Token is valid (permission: write).\n",
            "Your token has been saved to /root/.cache/huggingface/token\n",
            "Login successful\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Verify authentication\n",
        "from huggingface_hub import whoami\n",
        "whoami()\n",
        "# you should see something like {'type': 'user',  'id': '...',  'name': 'Wauplin', ...}"
      ],
      "metadata": {
        "id": "MMHkYq7oF6y4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5786e2d6-2b79-4075-b3d1-011b409796a8"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'type': 'user',\n",
              " 'id': '6404c20d3d49e1e066b97c10',\n",
              " 'name': 'jbatista79',\n",
              " 'fullname': 'Josue Batista',\n",
              " 'email': 'josue@josuebatista.com',\n",
              " 'emailVerified': True,\n",
              " 'canPay': False,\n",
              " 'isPro': False,\n",
              " 'periodEnd': None,\n",
              " 'avatarUrl': '/avatars/e686904a94e267b4570907a7e734fbb4.svg',\n",
              " 'orgs': [],\n",
              " 'auth': {'type': 'access_token',\n",
              "  'accessToken': {'displayName': 'Whisper Fine-Tuning', 'role': 'write'}}}"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Loading the audio dataset\n",
        "Here, we load the \"PolyAI/minds14\" dataset from Hugging Face's datasets library, specifying `en-US` as the language and `train` as the dataset split we wish to load. This dataset is designed for intent classification within spoken language understanding, a critical task in developing conversational AI.\n"
      ],
      "metadata": {
        "id": "9iv2OIvX7RI1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from datasets import load_dataset\n",
        "\n",
        "minds = load_dataset(\"PolyAI/minds14\", name=\"en-US\", split=\"train\")\n",
        "minds"
      ],
      "metadata": {
        "id": "j_L1_F8nuohR",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 304,
          "referenced_widgets": [
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            "b38842241bd042faa7991e6cc7d69fdf"
          ]
        },
        "outputId": "43218cef-9640-42be-fe83-6d343ec6baf1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/datasets/load.py:1461: FutureWarning: The repository for PolyAI/minds14 contains custom code which must be executed to correctly load the dataset. You can inspect the repository content at https://hf.co/datasets/PolyAI/minds14\n",
            "You can avoid this message in future by passing the argument `trust_remote_code=True`.\n",
            "Passing `trust_remote_code=True` will be mandatory to load this dataset from the next major release of `datasets`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading builder script:   0%|          | 0.00/5.90k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "cb2c9f1a4ed64319bc0f5d02e831a921"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading readme:   0%|          | 0.00/5.29k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7715aa724bf34750af9a878a829b4120"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading data:   0%|          | 0.00/471M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "da1afbba67d14a79b3fd48791bf48ffe"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating train split: 0 examples [00:00, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c7f833dc16ac491da5b4926d59918e9e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dataset({\n",
              "    features: ['path', 'audio', 'transcription', 'english_transcription', 'intent_class', 'lang_id'],\n",
              "    num_rows: 563\n",
              "})"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Displaying an example entry from the dataset\n",
        "To get a feel for the dataset's structure, we display the first entry. This gives us insight into the data's format, including the audio file's properties and any associated metadata, such as the transcription and intent classification."
      ],
      "metadata": {
        "id": "SEid7sQU7XWg"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "example = minds[0]\n",
        "for key, value in example.items():\n",
        "    print(f\"{key}: {value}\")"
      ],
      "metadata": {
        "id": "uHbT76n_7amq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "c823244b-0f50-44ed-fa9a-9393c90d8da6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "path: /root/.cache/huggingface/datasets/downloads/extracted/28aa727f91fee90575c34956bab09d1716cfaf460c6afcba86a10f04a7d58b83/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav\n",
            "audio: {'path': '/root/.cache/huggingface/datasets/downloads/extracted/28aa727f91fee90575c34956bab09d1716cfaf460c6afcba86a10f04a7d58b83/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav', 'array': array([ 0.        ,  0.00024414, -0.00024414, ..., -0.00024414,\n",
            "        0.        ,  0.        ]), 'sampling_rate': 8000}\n",
            "transcription: I would like to set up a joint account with my partner\n",
            "english_transcription: I would like to set up a joint account with my partner\n",
            "intent_class: 11\n",
            "lang_id: 4\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Mapping intent class IDs to descriptive labels\n",
        "This dataset includes numerical identifiers for intent classes. To make these identifiers more understandable, we map them to their descriptive labels, making it easier to interpret the data."
      ],
      "metadata": {
        "id": "1Y4DybQT7f_K"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "id2label = minds.features[\"intent_class\"].int2str\n",
        "id2label(example[\"intent_class\"])"
      ],
      "metadata": {
        "id": "RRko_mDI7jVa",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "3c9ec260-faa0-49b2-8ac8-2f78e6402448"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'joint_account'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Removing unnecessary columns from the dataset\n",
        "To streamline our dataset for analysis, we remove columns that are not needed for our current task, such as `lang_id` and `english_transcription`. This simplifies the dataset, focusing on the audio data and intent labels.\n"
      ],
      "metadata": {
        "id": "dx5Nfecu7vah"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "columns_to_remove = [\"lang_id\", \"english_transcription\"]\n",
        "minds = minds.remove_columns(columns_to_remove)"
      ],
      "metadata": {
        "id": "efg2k3oK7zHJ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Listening to an audio sample\n",
        "\n",
        "Now that we've loaded and inspected the dataset, let's listen to an audio example. This helps us understand the quality and content of the audio data we'll be working with."
      ],
      "metadata": {
        "id": "f7ZajJclyiMf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import Audio\n",
        "\n",
        "example = minds[6]\n",
        "wav_array = example[\"audio\"][\"array\"]\n",
        "sampling_rate = example[\"audio\"][\"sampling_rate\"]\n",
        "\n",
        "Audio(data=wav_array, rate=sampling_rate)"
      ],
      "metadata": {
        "id": "kXGqdrFP3a1B",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "outputId": "b6b98558-87e3-4358-d9dd-b14ad2e247eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
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type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Visualizing an audio signal\n",
        "Visualizing audio signals can provide valuable insights into their characteristics. Here, we plot the waveform of an audio sample, helping us to observe its amplitude variations over time. This visual representation is useful for understanding the audio data's structure and identifying patterns."
      ],
      "metadata": {
        "id": "2GfSJ9wd8KYw"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import librosa\n",
        "import matplotlib.pyplot as plt\n",
        "import librosa.display\n",
        "\n",
        "array = example[\"audio\"][\"array\"]\n",
        "sampling_rate = example[\"audio\"][\"sampling_rate\"]\n",
        "\n",
        "plt.figure().set_figwidth(12)\n",
        "librosa.display.waveshow(array, sr=sampling_rate)"
      ],
      "metadata": {
        "id": "vWU6HtHH09Ok",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 466
        },
        "outputId": "cd11ad16-58ee-4169-8bec-a1f348dd10d2"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<librosa.display.AdaptiveWaveplot at 0x7d91aa72fbe0>"
            ]
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x480 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Preprocessing the audio dataset for machine learning\n",
        "\n",
        "Before feeding audio data into machine learning models, it's essential to preprocess it. This section outlines the preprocessing steps necessary to transform the audio data into a format suitable for analysis and modeling. We'll cover casting the audio data to a consistent format, filtering recordings based on their duration to maintain uniformity, and extracting features that models can interpret. These preprocessing steps are vital for ensuring the quality and consistency of the input data, directly impacting the effectiveness of machine learning algorithms.\n"
      ],
      "metadata": {
        "id": "foY6E06WgsdQ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Cast audio column to uniform format\n",
        "To ensure that all audio data within our dataset adheres to a uniform format, we cast the `audio` column to a specific configuration using Hugging Face's `datasets` library. This step is crucial for maintaining consistency, especially when dealing with datasets that might contain audio files in various formats or sampling rates. Here, we standardize the audio data to a sampling rate of 16,000 Hz, which is a common rate used in speech recognition systems.\n"
      ],
      "metadata": {
        "id": "pOUDSjLX_Hoy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from datasets import Audio\n",
        "\n",
        "minds = minds.cast_column(\"audio\", Audio(sampling_rate=16000))"
      ],
      "metadata": {
        "id": "vVM1MlHg8F1Z"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Filter out long audio files\n",
        "In speech and audio processing tasks, it's often beneficial to work with audio files of a consistent duration. Longer audio files can be problematic due to increased computational requirements and potential irrelevance of parts of the audio. Here, we define a function to check if the audio's length is within a specified maximum duration. This function will later be used to filter out any audio files exceeding our defined maximum length, ensuring a more uniform dataset conducive to efficient processing."
      ],
      "metadata": {
        "id": "uMhAbmGL_QKx"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "MAX_DURATION_IN_SECONDS = 10.0\n",
        "\n",
        "def is_audio_length_in_range(input_length):\n",
        "    return input_length < MAX_DURATION_IN_SECONDS"
      ],
      "metadata": {
        "id": "TZRBIfIP9QI6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "new_column = []\n",
        "\n",
        "for i, example in enumerate(minds):\n",
        "    # print(i)\n",
        "    # print(example[\"audio\"][\"path\"])\n",
        "    audio_array = example[\"audio\"][\"array\"]\n",
        "    sr = example[\"audio\"][\"sampling_rate\"]\n",
        "    duration = librosa.get_duration(y=audio_array, sr=sr)\n",
        "    new_column.append(duration)\n",
        "    # print(f\"{duration:.2f}s\")\n",
        "    # if i == 5:\n",
        "    #     break\n",
        "\n",
        "minds = minds.add_column(\"duration\", new_column)\n",
        "# Printing the duration for 5 audio samples\n",
        "for i, example in enumerate(minds):\n",
        "    # print(i)\n",
        "    # print(example[\"audio\"][\"path\"])\n",
        "    print(example[\"path\"])\n",
        "    print(example[\"duration\"])\n",
        "    if i == 5:\n",
        "        break"
      ],
      "metadata": {
        "id": "Pt9I2KqCYroC",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0a2e2d6d-f8dd-44e0-c621-b1a8745496ed"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/root/.cache/huggingface/datasets/downloads/extracted/28aa727f91fee90575c34956bab09d1716cfaf460c6afcba86a10f04a7d58b83/en-US~JOINT_ACCOUNT/602ba55abb1e6d0fbce92065.wav\n",
            "10.837375\n",
            "/root/.cache/huggingface/datasets/downloads/extracted/28aa727f91fee90575c34956bab09d1716cfaf460c6afcba86a10f04a7d58b83/en-US~JOINT_ACCOUNT/602baf24bb1e6d0fbce922a7.wav\n",
            "6.656\n",
            "/root/.cache/huggingface/datasets/downloads/extracted/28aa727f91fee90575c34956bab09d1716cfaf460c6afcba86a10f04a7d58b83/en-US~JOINT_ACCOUNT/602b9f97963e11ccd901cc32.wav\n",
            "24.234625\n",
            "/root/.cache/huggingface/datasets/downloads/extracted/28aa727f91fee90575c34956bab09d1716cfaf460c6afcba86a10f04a7d58b83/en-US~JOINT_ACCOUNT/602bacab5f67b421554f6488.wav\n",
            "3.242625\n",
            "/root/.cache/huggingface/datasets/downloads/extracted/28aa727f91fee90575c34956bab09d1716cfaf460c6afcba86a10f04a7d58b83/en-US~JOINT_ACCOUNT/602b9d4cbb1e6d0fbce91fa4.wav\n",
            "3.84\n",
            "/root/.cache/huggingface/datasets/downloads/extracted/28aa727f91fee90575c34956bab09d1716cfaf460c6afcba86a10f04a7d58b83/en-US~JOINT_ACCOUNT/602bafa0bb1e6d0fbce922c7.wav\n",
            "4.551125\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Apply length filter to dataset\n",
        "With our length filter function defined, we now apply it to our dataset. Using the `filter` method provided by the `datasets` library, we can efficiently remove entries that don't meet our duration criteria. This step iterates through the dataset, applying our `is_audio_length_in_range` function to each entry and retaining only those that fit within our specified maximum duration. This filtering process is a key step in preparing our dataset for subsequent analysis and modeling.\n"
      ],
      "metadata": {
        "id": "CeCDiNic_xDa"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# use 🤗 Datasets' `filter` method to apply the filtering function\n",
        "minds = minds.filter(is_audio_length_in_range, input_columns=[\"duration\"])\n",
        "\n",
        "# remove the temporary helper column\n",
        "minds = minds.remove_columns([\"duration\"])\n",
        "minds"
      ],
      "metadata": {
        "id": "6ToNuFgm9UG4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 118,
          "referenced_widgets": [
            "7f6a2b6202c4412c9574538006e68fcb",
            "d014dbaa21274809855052a887a6f10a",
            "ab9a92af54cd408989650e47aef3fb3a",
            "2618b8658e75416d9566c4ad8714c3db",
            "3f02196ca9954414ac55e2fb8d366ffb",
            "be5f2f25fa084050add7bfa686e46b4c",
            "067123c1fb3d41e59166b430172099d5",
            "0d2e97f81a234caba64a0b4e16c7a589",
            "7632ca4fcfeb449ba92071e3d577bfd0",
            "2f5f4bd95e354ae083fa8e609248f27e",
            "202572c5d12941bc8297e835f1b59a70"
          ]
        },
        "outputId": "52b5779d-7873-4b9c-f0f9-859c85b3cd66"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Filter:   0%|          | 0/563 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "7f6a2b6202c4412c9574538006e68fcb"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dataset({\n",
              "    features: ['path', 'audio', 'transcription', 'intent_class'],\n",
              "    num_rows: 417\n",
              "})"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Feature extraction with WhisperFeatureExtractor\n",
        "Before we can transcribe audio data or use it for training machine learning models, we often need to extract relevant features from the raw audio. This process transforms audio data into a format that models can more easily interpret. Here, we utilize the `WhisperFeatureExtractor` from the `transformers` library to prepare our dataset for the Whisper model. The feature extractor standardizes the audio data, ensuring it's in the correct format and sampling rate expected by Whisper for efficient transcription."
      ],
      "metadata": {
        "id": "x1FoXNdk_ew1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import WhisperFeatureExtractor\n",
        "\n",
        "feature_extractor = WhisperFeatureExtractor.from_pretrained(\"openai/whisper-small\")"
      ],
      "metadata": {
        "id": "gjGV9FnB7a0q",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "5fce160bea674c0b91e502054935c428",
            "e9ddc55420d7487e8b78f188cd6f3b63",
            "8a413439bcc84b9cb18cc79f58f645a1",
            "d8c9fd7beaab418eb39589db8ec9da67",
            "643baf1b7c044b7dad040955d25359a0",
            "7a1b4ae862894d34955c6f22e6aca895",
            "fb6ebed185064b41ad73eb08cb0fc8de",
            "6cebbfefa9bd4acf855c662df9ece6e9",
            "057da4db4eb7408688779ff93b42f937",
            "2d0afccd6aad4070b3276edd52798a93",
            "5f04aad3122c49be962258720fccd3ae"
          ]
        },
        "outputId": "b49a8f91-cdcf-40a9-81aa-7684377d63fb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "preprocessor_config.json:   0%|          | 0.00/185k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "5fce160bea674c0b91e502054935c428"
            }
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Prepare dataset for Whisper model\n",
        "To process our audio data with the Whisper model, we must first prepare it according to the model's requirements. This involves applying the `WhisperFeatureExtractor` to each audio file in our dataset. We define a `prepare_dataset` function that takes an example from our dataset, extracts its audio, and then applies the feature extractor. This function is mapped over the entire dataset, transforming each audio file into a format suitable for transcription with Whisper. This step is crucial for leveraging Whisper's capabilities to transcribe or analyze our audio data.\n"
      ],
      "metadata": {
        "id": "f9fYO2yAAAh7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def prepare_dataset(example):\n",
        "    audio = example[\"audio\"]\n",
        "    features = feature_extractor(\n",
        "        audio[\"array\"], sampling_rate=audio[\"sampling_rate\"], padding=True\n",
        "    )\n",
        "    return features"
      ],
      "metadata": {
        "id": "SwMbnwit7h3A"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "minds = minds.map(prepare_dataset)\n",
        "minds"
      ],
      "metadata": {
        "id": "vA8REAyC7nVJ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 118,
          "referenced_widgets": [
            "5ec95a60760d4ee6b245dd5020d296e5",
            "d69ef763d1e946e3a26f23510fb5f343",
            "ac6ec6ecc7a14c4c81485624d4c7656d",
            "4cd675b3b47741f29a7f5b41b3325e55",
            "5d0e3bb4414c42e8a12d587d8bac741e",
            "9bf33f5741ae46848e7f3dac87cc5533",
            "9bdb4f6c8c8048aa9692f412ff2e18f2",
            "d0e6c459d629409b8a57ceec2c147a7e",
            "51c1fb4830594158a8ea52d97755bed8",
            "6e1b37e9220a478796e81ec7a67ec462",
            "ecb8c5524aea4ea59ba69d0deb51b593"
          ]
        },
        "outputId": "66bd1544-8254-40ac-ae7f-e0e77f505a0f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Map:   0%|          | 0/417 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "5ec95a60760d4ee6b245dd5020d296e5"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Dataset({\n",
              "    features: ['path', 'audio', 'transcription', 'intent_class', 'input_features'],\n",
              "    num_rows: 417\n",
              "})"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Visualizing preprocessed audio features\n",
        "After preprocessing our audio data, it's helpful to visualize the resulting features to understand what the Whisper model will \"see\" when analyzing the audio. Here, we select an example from our preprocessed dataset and plot its features. This visualization can give us insight into the nature of the transformations applied by the `WhisperFeatureExtractor` and how they might influence the model's performance on our audio data.\n"
      ],
      "metadata": {
        "id": "hZziQfd0AOKz"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import librosa\n",
        "import librosa.display\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "example = minds[0]\n",
        "input_features = example[\"input_features\"]\n",
        "\n",
        "plt.figure(figsize=(12, 8))\n",
        "librosa.display.specshow(\n",
        "    np.asarray(input_features[0]),\n",
        "    x_axis=\"time\",\n",
        "    y_axis=\"mel\",\n",
        "    sr=feature_extractor.sampling_rate,\n",
        "    hop_length=feature_extractor.hop_length,\n",
        ")\n",
        "\n",
        "plt.colorbar(format='%+2.0f dB')\n",
        "plt.xlabel('Time')  # Setting x-axis label\n",
        "plt.ylabel('Mel Frequency')  # Setting y-axis label\n",
        "plt.title('Mel Spectrogram')  # Optionally, add a title\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "vLHJ9_zB7F-7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 718
        },
        "outputId": "3f0d6ed8-5bc4-49da-ef99-79c720617179"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1200x800 with 2 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "example = minds[0]\n",
        "for key, value in example.items():\n",
        "    if key == 'input_features':  # Skip 'input_features'\n",
        "        continue\n",
        "    print(f\"{key}: {value}\")"
      ],
      "metadata": {
        "id": "ZJKWsTMafwvq",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8d4697ad-6635-4346-f354-72fdd877355c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "path: /root/.cache/huggingface/datasets/downloads/extracted/28aa727f91fee90575c34956bab09d1716cfaf460c6afcba86a10f04a7d58b83/en-US~JOINT_ACCOUNT/602baf24bb1e6d0fbce922a7.wav\n",
            "audio: {'path': None, 'array': array([-3.05175781e-05,  1.22070312e-04,  2.44140625e-04, ...,\n",
            "        1.30310059e-02,  1.11389160e-02,  5.67626953e-03]), 'sampling_rate': 16000}\n",
            "transcription: Henry County set up a joint account with my wife and where are they at\n",
            "intent_class: 11\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Leveraging Whisper for audio to text transcription\n",
        "\n",
        "OpenAI's Whisper model represents a breakthrough in audio to text transcription technology, offering a powerful tool for converting spoken language into written text. This section guides you through the process of using the Whisper model to transcribe audio data. We'll explore two approaches: one using raw numpy arrays and another utilizing WAV files. By understanding these methods, you'll be equipped to transcribe audio data efficiently, a skill applicable in various domains, including voice recognition and natural language understanding.\n",
        "\n",
        "To transcribe audio to text using OpenAI's Whisper model, you'll first need to ensure you have Whisper installed and then proceed with the Python code to load and transcribe the audio.\n",
        "\n",
        "### Step 1: Install Whisper\n",
        "\n",
        "First, ensure that you have OpenAI's Whisper installed:"
      ],
      "metadata": {
        "id": "XxqYaP5WOijy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture\n",
        "!pip install -q cohere openai tiktoken\n",
        "!pip install -q git+https://github.com/openai/whisper.git"
      ],
      "metadata": {
        "id": "f2ieuqiJSVLD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "### Step 2: Load your audio data\n",
        "\n",
        "Let's use audio data from the `example` dataset, loaded into `wav_array` with a sampling rate defined as `sampling_rate`. This is great because Whisper needs the audio data in a format it can process."
      ],
      "metadata": {
        "id": "tGlhK-3jO8Ak"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import Audio\n",
        "\n",
        "example = minds[200]\n",
        "wav_array = example[\"audio\"][\"array\"]\n",
        "sampling_rate = example[\"audio\"][\"sampling_rate\"]\n",
        "\n",
        "Audio(data=wav_array, rate=sampling_rate)"
      ],
      "metadata": {
        "id": "HwjJNp2Sf2F6"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "\n",
        "### Step 3a: Transcribe audio to text using numpy and Whisper\n",
        "\n",
        "In this example, audio data is converted to float32 before passing it to the model.transcribe() function. Here's how you can do it:"
      ],
      "metadata": {
        "id": "xODbkhLMPWn0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# NLTK helps to split the transcription sentence by sentence\n",
        "# and shows it in a neat manner one below another. You will see it in the output below.\n",
        "\n",
        "import nltk\n",
        "nltk.download('punkt')\n",
        "from nltk import sent_tokenize"
      ],
      "metadata": {
        "id": "I0kHXcHTLoAA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import whisper\n",
        "import numpy as np\n",
        "\n",
        "# Assuming wav_array is your audio data and sampling_rate is defined\n",
        "\n",
        "# Convert wav_array to float32\n",
        "wav_array = wav_array.astype(np.float32)\n",
        "\n",
        "# Initialize the Whisper model\n",
        "model = whisper.load_model(\"small\")  # Adjust model size as needed\n",
        "\n",
        "# Transcribe the audio\n",
        "result = model.transcribe(audio=wav_array)\n",
        "\n",
        "# Display the transcription\n",
        "print(\"Transcription:\")\n",
        "for sent in sent_tokenize(result['text']):\n",
        "  print(sent)"
      ],
      "metadata": {
        "id": "gdbpEFpVLEjI"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "### Step 3b: Transcribe audio to text using WAV file and Whisper\n",
        "\n",
        "In this example, we save the wav_array to a .wav file before transcribing. Here's how you can do it:"
      ],
      "metadata": {
        "id": "WrAEPCJiQ6CU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import soundfile as sf\n",
        "\n",
        "# Save your wav_array to a file\n",
        "sf.write('temp_audio.wav', wav_array, sampling_rate)\n",
        "\n",
        "# Now transcribe the saved audio file\n",
        "result = model.transcribe('temp_audio.wav')\n",
        "\n",
        "# Print the transcription\n",
        "print(\"Transcription:\")\n",
        "for sent in sent_tokenize(result['text']):\n",
        "  print(sent)"
      ],
      "metadata": {
        "id": "PvDSKkjjKvaC"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Gratitude\n",
        "\n",
        "Many thanks to Naval Katoch for his valuable insights."
      ],
      "metadata": {
        "id": "1_qasqaAKHPR"
      }
    }
  ]
}